BIG DATA ANALYTICS WITH MACHINE LEARNING FOR IOT SENSED DATA

Abstract

Internet of things (IoT) is the most encouraging automation technology and it producing large amount of sensed data. It is not possible to process this data by humans. Big data technology come out as a key data analytics conception that magically process the data for required outputs and actions. Internet of things means connecting things that are present in the world with internet. Big data is important as many public and private organizations gather huge amounts of domain-specific information,which may contain useful information on issues such as intelligence, cyber security, fraud detection, marketing and medical
information.Investigation of the enormous data demands more effort for different quantity to take out the awareness for the determination. Machine learning is the best way to know about hidden relationships between data, because it works with a scale machine and works well with a large data set. Big data Analytics and deep learning are two areas that focus heavily on data science. Deep learning algorithms produce high-quality, robust inferences such as data support for a hierarchical learning process. This paper gives comprehensive view about machine learning contributions in processing IoT sensed data with big data analytics. This research work shows the big data algorithms and analytics toolsthat are effectively analyze the data of resource constrained IoT Sensed data.